Metadata-Version: 2.1
Name: deciplot
Version: 0.0.1
Summary: A handy tool that helps you better visualize your data by plotting 2D decision boundaries, using any sklearn classifier models.
Home-page: https://github.com/hxt365/Deciplot
Author: Truong Hoang
Author-email: hxt365@gmail.com
License: UNKNOWN
Description: # Deciplot
        This is a handy tool that helps you better visualize your data by plotting 2D decision boundaries, using any sklearn classifier models.
        
        ## Installation
        Run the following to install:
        ```python
        pip install deciplot
        ```
        
        ## Usage
        ```python
        from sklearn.datasets import load_iris
        from sklearn.tree import DecisionTreeClassifier
        from deciplot import DeciPlot2D
        
        # Get iris dataset from sklearn
        iris = load_iris()
        X, y, feature_names, target_names = iris['data'], iris['target'], iris['feature_names'], iris['target_names']
        
        # Initialize a classifier model for plotting decision boundaries
        dtree = DecisionTreeClassifier()
        
        # Initialize an DecPlot2D object
        dp2d = DeciPlot2D(X, y, feature_names, target_names, dtree)
        
        # Plot and visualize decision boundaries
        dp2d.plot(figsize=(20, 10))
        ```
        After running this code, we'll get this beautiful plot:
        <p align="center">
        <img src='https://user-images.githubusercontent.com/16115992/97473857-8391fb00-195c-11eb-9e14-d6c022c2aec4.png' alt='Decision boundary plot' height=400px/>
        </p>
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
